Quantum Computing Is a Technology to Watch for Supply Chain
Supply chain people know better than anyone how messy reality can get. Quantum computing is a tool that can help to quantify the mess – and channel it into resilience. Add quantum computing to the list of things your innovation teams should track to future-proof your supply chain strategy.
Zara’s parent company, Inditex, is an admired innovator in supply chain management, so when quantum computing came up over a dinner conversation in October, my ears perked up. They were experimenting with quantum simulations of synthetic molecules to enable the chemical recycling of clothing – a potential sustainability breakthrough for the apparel industry.
Quantum computing is different from classical computing because its logic builds on qubits, which can exist in multiple states at the same time, unlike binary digits or bits, which can only exist as one or zero. This matters because reality, as described by Niels Bohr’s quantum mechanics, doesn’t reliably fit the simulations we build with traditional digital computers in our planning and scenario management tools.
No one knows better than supply chain people just how messy reality can get, so any tool that helps us get closer to quantifying it is worth a look.
Long Term Hopes
The implications for digital leaders in supply chain include at least three use cases that merit attention on your five-year roadmap:
- Material science innovation as a path to better manufacturing, especially for circularity.
- Molecular design for faster drug development and innovative chemical process engineering.
- Hybrid quantum/classical computer simulations for ML modeling of super complex systems to build next-gen digital twins in automotive design, global logistics network configurations, and large-scale operations.
Each of these areas is already being explored by leading companies, including Dow, BMW, Hewlett Packard, BASF, Moderna, and Novartis, as well as Inditex. Few, if any, seem to have moved past experimentation, but some examples from the world of pure research promise to make a big difference.
One such example is a collaboration between Accenture, Intel, AWS, and Good Chemistry, a Canadian software startup that uses quantum computing and AI for “quantum chemistry.” The team’s goal was to find cost-effective ways to break down the bonds in “forever chemicals” (aka PFAS or polyfluoroalkyl substances used in packaging, paint, and waterproofing), which are known to be carcinogenic and abundant in the environment.
The core of the challenge was computational, described in a paper written by the team’s leaders as a “quantum-mechanical problem of solving the electronic Schrödinger equation… An accurate solution to this problem can be obtained using numerically exact methods such as full configuration interaction (FCI). However, those calculations have always been intractable due to their computational complexity. An FCI calculation is only possible for tiny molecules, consisting of a few atoms, using small basis sets on the largest supercomputers available.”
Cutting to the chase… the team did solve the Schrödinger equation and, in the process, demonstrated much of what is exciting about quantum computing for supply chain leaders. Above all, it is the unique ability to simulate the most complex systems and render insights fast enough to act in a business-relevant time horizon.
You Are Not Yet Behind
I saw a presentation in 2019 by Fernando Brandao, Professor of Theoretical Physics at Caltech, and was blown away by the prospect of quantum computing as applied to supply chain and operations. Four full years later, the technology, although promising, remains beyond the horizon for most.
One problem is the high error rate of quantum computing due to the imperfect quality of the hardware. This includes the qubits themselves, which come in various forms (superconducting qubits, trapped ion qubits, neutral atom qubits) and refrigeration equipment needed to keep the system close to absolute zero. Companies like IBM and Google are working on this, along with startups and universities, but we are still in the early days.
In 2019, Brandao argued that the flywheel driving hardware improvement depends on developing and learning from more use cases, which the world of supply chain is just now waking up to. In fact, of the nearly 200 companies Zero100 tracks in our digital talent data set, only 11% have any mention of “quantum” in supply chain job descriptions. The few who do (BMW, PepsiCo, Pfizer) feature it in specialized research and innovation roles alongside other emerging tech categories.
Add quantum computing to the list of things research and innovation teams should track, and you’ll be covered.
At least for now.